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Experimental Vs Theoretical

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Preview of Dynamics, Neural Collapse, and Normalization in Deep Classifiers Trained with Square Loss
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Dynamics, Neural Collapse, and Normalization in Deep Classifiers Trained with Square Loss (JMLR__2021-22.pdf)

4.61 MBEN 18 pages
This memo explores the dynamics of deep classifiers trained with square loss, revealing convergence to minimum norm solutions when both Weight Decay and Batch Normalization are employed. The study highlights the importance of these techniques for stable training, demonstrating...
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